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Post Doctoral Fellow

Abu Dhabi, United Arab Emirates
Closing date
17 Dec 2023

About Khalifa University

Khalifa University is ranked 181st in the QS World University Rankings 2023, and the top University in the UAE, with a range of research and academic programs designed to address the entire range of strategic, scientific and industrial challenges facing our rapidly evolving world.

Its world-class faculty and state-of-the-art research facilities provide an unparalleled learning experience to students from the UAE and around the world. Our research and academic activities cover a broad range of disciplines in engineering, science and medicine through our three colleges.

Khalifa University’s research relates to key focus sectors of relevance to the UAE’s strategic economic growth and the technology platforms that serve as foundations for these sectors. The University’s research priorities are addressed in two categories “verticals” and “horizontals”  which jointly cover specific industry and sector needs, technical platforms and expertise.

KU’s focus sectors are Clean and Renewable Energy, Hydrocarbon Exploration and Production, Water and Environment, Healthcare, Aerospace, and Supply Chain and Logistics. Research in these sectors is enhanced by our research platforms of Robotics, AI and Data Science, Information and Communication Technologies, and Advanced Materials and Manufacturing as well as Fundamental Sciences.

Position Overview

KU is seeking a highly motivated Post-Doctoral Fellow to work on an interdisciplinary research project that focusses on the low-cost mechanosynthesis of organic molecular compounds for optoelectronic materials and energy storage applications. The Post-Doctoral Fellow will have completed a PhD in computational materials modelling in chemistry, natural sciences, physics, chemical engineering or related disciplines. The right candidate is expected to work within a large group comprising chemists and engineers and perform in-silico computational structure prediction (CSP) on a range of target compounds of interest to experimentalists. The calculated structures will then be used as starting points for property predictions and structure-property correlations. The aim will be to develop an end-to-end workflow for computing the optoelectronic and energy storage properties of candidate solid materials so as to support experimentalists with their research efforts.

The right candidate will have hands-on experience with performing periodic density functional theory (DFT) calculations of molecular crystals using VASP, CASTEP or both. Competence in the python programming language and familiarity with working in a HPC environment is a must. The ideal candidate will also have experience of applying supervised and unsupervised machine learning (ML) techniques for materials discovery. Excellent scientific writing and oral communication skills is a must. The ability to work to tight deadlines is a must. Familiarity with computational structure prediction methods is ideal but not required.

As part of the project, the researcher will have access to state-of-the-art computational modelling resources including a well-equipped HPC and various solid-state modelling packages and codes (some commercial and some developed at the PIs lab over several years). The position comes with excellent benefits and the ability for progression subject to excellent performance during the period of the project.

Position Requirements

  • Perform computational materials modelling research (DFT, MD, CSP) as directed by the Line Manager
  • Work diligently to meet deadlines as set by the Line Manager
  • Support graduate students with their research as directed by the Line Manager
  • Disseminate research findings in papers, conferences and as directed by the Line Manager
  • Adhere to the University's information security and confidentiality policies and procedures, and report breaches or other security risks accordingly
  • Perform any other tasks assigned by the Line Manager


Candidate Profile

Essential Criteria

  • PhD from a reputable university in Computational Materials Modelling (Chemistry, Natural Sciences, Physics, Chemical Engineering or related disciplines);
  • Experience of independent writing of scientific papers;
  • A willingness to maintain and contribute to a collegial, collaborative and supportive research culture and atmosphere in the PIs lab;
  • Excellent command of the English language and demonstrated ability to communicate using scientific English in written and oral settings;
  • Ability to work both independently and as part of an interdisciplinary team of researchers;
  • The proven ability to work on multiple tasks with competing demands and complete all assigned tasks to a high standard within the requested deadlines;
  • Ability to train and mentor undergraduate and graduate students and support fellow researchers in the group;
  • Evidence of highly developed reasoning and problem-solving skills.

Desired Criteria

  • PhD gained from a top 200 QS or THE ranked University;
  • At least 1-2 years of post-PhD relevant research experience in academia or in industry;
  • At least 1-3 high impact first-author publications in top 10% journals in the relevant field.

Should you require further assistance or if you face any issue with the online application, please feel to contact the Recruitment Team (

Primary Location: Abu Dhabi UAE
Job: Post Doctoral Fellow
Schedule: Regular
Shift: Standard
Job Type: Full-time

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